MULTI-PERIOD HEAT EXCHANGER NETWORK RETROFIT UNDER FOULING EFFECTS.

MULTI-PERIOD HEAT EXCHANGER NETWORK RETROFIT UNDER FOULING EFFECTS. Supapol Rangfak a, Kitipat Siemanond a* a The Petroleum and Petrochemical College, Chulalongkorn University, Bangkok, Thailand Keywords: Retrofit; HENs; Optimization; Fouling; Multi-period. ABSTRACT Heat exchanger networks (HENs) are important to industrial because they manage heat transfer between hot and cold process streams, resulting in reduction of operating cost. The accumulation of fouling deposits on heat transfer surface area of exchanger causes more energy usage. In order to decrease extra utilities cost, regarding fouling with multi-period in HEN is proposed to HEN retrofit. The model of HEN retrofit represented here is based on stage-wise superstructure by Yee and Grossmann (1990) with non-isothermal mixing assumption. In order to solve large-scale problems, the sequential initialization techniques by complex mixed integer nonlinear programming (MINLP) are required. There are four main initialization steps; MILP, NLP, MINLP and relocation steps. The multi-period HEN retrofit is to find the HEN design consuming optimal hot and cold utilities and operating under fouling-accumulation periods of twelve months before annual cleaning. * Kitipat.S@chula.ac.th INTRODUCTION Many petroleum and petrochemical plants need to be improved for saving more energy and gaining more profit. The retrofit of HEN is an important way to improve energy efficiency in the process. There are various strategies to achieve energy savings in retrofit, for instance, pinch technology or the heat integration that has been researched for several decades. In 1990, Yee and Grossmann proposed methods to synthesize HEN by MINLP optimization for both capital and operating costs. Furthermore, BjÖrk and Westerlund (2002) studied truly optimal network configuration with non-isothermal mixing assumption. Instead of modeling only an overall heat balance around each stage, nonlinear heat balances around each exchanger and heat mixing equations will be added to allow nonisothermal mixing assumption One of the main problem in crude preheat train caused by fouling deposits is the reduction of thermal and hydraulic efficiency in the exchangers. Consequently, the increasing capital and operating costs from the energy consumption, and extra exchanger maintenance and cleaning cost using antifouling additives, including loss of production can occur. The HEN retrofit under fouling effect is interesting way to reduce extra utility cost. The purpose of this study is to retrofit HENs from petrochemical processes. The model is formulated based on a stage-wise superstructure of Yee and Grossmann with initialization method, non-isothermal mixing assumption and regarding fouling effects. Petrochemical and Materials Technology Tuesday May 23, 2017, Pathumwan Princess Hotel, Bangkok, Thailand Page 1

IMPROVEMENT MODEL AND STRATEGY A. Hen Retrofit Model with Fouling Effects The models of HEN retrofit in this study are represented by stage-wise superstructure with non-isothermal mixing assumption, as illustrated in Figure1. The HEN synthesis model by Yee and Grossmann is modified to HEN retrofit model. The constraint for existing exchanger matches in base-case HEN is required and added to the synthesis model, using binary variables. The objective function of HEN retrofit model is to maximize net present value (NPV) by maximizing utility saving cost and minimize total investment cost from both new exchangers and additional area which are nonlinear equations. Therefore, this study will be solved by MINLP model. Major assumptions in the proposed method include the following: Constant heat capacity flow rates of hot and cold fluids. Counter current heat exchangers. Non-isothermal mixing. Figure 1. Stage-wise superstructure of HEN (Yee and Grossmann, 1990) Yee and Grossmann s model is presented as comprehensive simultaneous model for heat integration. In order to avoid numerical difficulties from non-convex terms, the Chen approximation term (1987) of logarithmic mean temperature difference (LMTD) is used for exchanger area calculation. In addition, non-isothermal mixing concept of BjÖrk and Westerlund (2002) is applied to this model to find truly optimal network configuration. In additions, Fouling threshold model of Polley et al (2002) is appeared for more realistic model. When fouling deposits, it means resistance of fouling ( ) has increased. Consequently, overall heat transfer coefficient (U) will also be reduced corresponding to heat recovery rate. The equations for retrofit model are shown below: Petrochemical and Materials Technology Tuesday May 23, 2017, Pathumwan Princess Hotel, Bangkok, Thailand Page 2

B. HENS Retrofit Strategy under Twelve-months With Fouling Effects. This HEN retrofit strategy is divided into 3 steps, shown in Figure 2. For step 1, base-case HEN is operated under fouling effects for 12 months by Microsoft Excel spread sheet for determining the fouling rate and heat transfer behaviour of base-case HEN at the end of twelve months period. For step 2, base-case HEN at the end of twelve months period is retrofitted by retrofit model using GAMS software. The initialization strategy is needed to drive our solution of retrofitted HEN to optimum is presented in step 2. It contains of 3 inside steps; MILP, NLP and MINLP. For the first inside step, the objective function of MILP model is to find only optimal HEN topology without considering exchanger area. Nonlinear equations of LMTD and exchanger area cost do not appear in this step. Exchanger matching (as binary variables, z i,j,k ) are solved from this first step. For the second inside step, NLP model is used to find optimal HEN topology considering exchanger area. Binary variables from previous step are used as the initial values. For finding optimal split fraction, nonlinear equations are needed (continuous variables between 0-1; sph i,j,k and spc i,j,k ) in term of heat exchangers area. For Third inside step, MINLP model is used to find optimal retrofitted HEN considering both exchanger matching and area. Some variables from first and second inside steps are used as the initial values at this step. For the last step of this strategy, the optimal retrofitted HEN from step 2 is operated for 12 months by Microsoft Excel spread sheet to get the heat transfer behaviour, and the total NPV. The assumption of HEN operation is five years operation with annual cleaning. Petrochemical and Materials Technology Tuesday May 23, 2017, Pathumwan Princess Hotel, Bangkok, Thailand Page 3

Figure 2. Method for HEN retrofit model under fouling effects RESULTS AND DISCUSSION Our case study is crude preheat train which is retrofitted with initialization method regarding fouling effects. Our proposed HEN retrofit model is solved by using DICOPT solver in GAMS 24.2.1 on notebook computer (Dell INSPIRON N5110 (Intel Core i7-2630m CPU @ 2.00GHz, 6GB of RAM, Windows 7 Ultimate 64-bit Operating system)). The assumptions are constant heat capacities, constant heat transfer coefficients, nonisothermal mixing and counter-current flow in heat exchangers. Project life (n) is five years with 10% of annual interest rate. Hot and cold utility costs equal to $120 and $20 per kw-y, respectively. Heat exchanger area cost equation is shown below: Heat exchanger cost ($) = 26460 + 389*[area (m 2 )] 0.83 (19) Crude preheat train HEN involves 10 hot and 3 cold process streams with 6 existing exchangers as shown in Figure 4a. At the beginning, there were 67,988 and 75,076 kw of hot and cold utility usages, respectively with no fouling occurrence. During twelve months, fouling has occurred in all exchangers except exchanger 5. Therefore, total hot and cold utility consumptions reach to 71,406 kw and 78,494 kw, respectively. Consequently, annual exchanger cleaning is needed to recover heat-transfer efficiency. EMAT used in this retrofitted model is 0.09. The result of HEN retrofit model under fouling increasing total exchanger area from 3,913m 2 to 24,102m 2 as shown in Figure 4c and 4d. At the beginning, retrofitted HEN consumed hot and cold utilities of 46,492 kw and 53,580 kw, respectively. After 12 months, overall heat transfer coefficient dropping off in all exchangers due to increasing fouling deposition rate except exchanger 5 as shown in Figure 3. Consequently, total hot and cold utility consumptions approach 58,712 kw and 65,800 kw, respectively. Comparing to the base-case as presented in Figure 4, retrofitted HEN with fouling effects can save hot and cold utilities 18.38% and 20.22%, respectively. Total NPV of this HEN for five years is $5,744,783. Petrochemical and Materials Technology Tuesday May 23, 2017, Pathumwan Princess Hotel, Bangkok, Thailand Page 4

3a) Base-case 3b) Existing exchangers of retrofitted-case 3c) New exchangers of retrofitted-case Figure 3. Fouling rate of exchangers in Crude oil preheat train 4a) Base-case HEN at initial (hot duty = 67,988kW, cold = 75,076kW) Petrochemical and Materials Technology Tuesday May 23, 2017, Pathumwan Princess Hotel, Bangkok, Thailand Page 5

4b) Base-case HEN at month 12 (hot duty = 71,406kW, cold = 78,494kW) 4c) Retrofitted-case HEN at initial (hot duty = 46,492 kw, cold = 53,580 kw) 4d) Retrofitted-case HEN at month 12 (hot duty = 58,712 kw, cold = 65,800kW) CONCLUSIONS Figure 4. HENs of Crude preheat train under fouling effects It has been shown that retrofit model with initialization method help save utility for case study from industrial process. Crude preheat train can save operating cost more than one million dollars per year. Moreover, retrofitted case with fouling effects can reduce the extra utilities usages under fouling deposition and approach high NPV in long period NOMENCLATURE Indices i hot process stream j cold process stream k index for stage 1... K base base case Sets HP = {i i is a hot process stream} HU = hot utility CP = {j j is a cold process stream} CU = cold utility Parameters FCp heat capacity flow rate(kw/ C) TIN inlet temperature ( C) TOUT outlet temperature ( C) Binary variable z existence of matching zcu cold utility exchanging zhu hot utility exchanging 1 matching 0 otherwise Variables q heat exchanged between hot and cold process stream (kw) qcu heat exchanged between hot stream and cold utility (kw) qhu heat exchanged between hot utility and cold stream (kw) t temperature of process stream( C) Petrochemical and Materials Technology Tuesday May 23, 2017, Pathumwan Princess Hotel, Bangkok, Thailand Page 6

hh film coefficient of hot stream(kw/ C.m 2 ) hc film coefficient of cold stream (kw/ C.m 2 ) an upper bound for heat exchanges Γ max possible approach temperatures C area cost coefficient($/m 2 ) CCU per unit cost for cold utility($/kw.year) CHU per unit cost for hot utility($/kw.year) CF fixed charge for exchangers($) B exponent for area cost α,β,γ dimensional parameters that vary for different substances (m 2. C/kW) E activation energy (kj/mol) ACKNOWLEDGEMENTS T w sph spc dth dtc thso tcso wall temperature of process stream ( C) split ratio of hot stream split ratio of cold stream approach temperature in the hot end( C) approach temperature in the cold end( C) temperature for the part of hot process stream( C) temperature for the part of cold process stream( C) a heat exchangers area(m 2 ) acu heat exchangers area of cold utility(m 2 ) ahu heat exchangers area of hot utility (m 2 ) Re Pr Reynolds number Prandltr number Authors would like to express our gratitude to The Petroleum and Petrochemical College, Chulalongkorn University, National Centre of Excellence for Petroleum, Petrochemicals and Advanced Material (PETROMAT), and Government Budget Fund for funding support. REFERENCES BjÖrk, K.-M., and Westerlund, E. (2002), Global optimization of heat exchanger network synthesis problems with and without the isothermal mixing assumption. Computers & Chemical Engineering 26, 1581-1593. Polley, G.T., Wilson, D.I., Yeap, B.L. and Pugh, S.J. (2002a), Evaluation of laboratory crude oil threshold fouling data for application to refinery pre-heat trains. Applied Thermal Engineering 22(7), 777-788. Yee, T.F. and Grossmann, I.E. (1990), Simultaneous optimization models for heat integration II. Heat exchanger network synthesis. Computers & Chemical Engineering 10(14), 1165-1184. Petrochemical and Materials Technology Tuesday May 23, 2017, Pathumwan Princess Hotel, Bangkok, Thailand Page 7